Hello,
I just finished the “Regularization and bias/variance” lecture video. So far, I have an impression that cross-validation helps avoid both high bias and high variance, while regularization helps avoid only high variance. Is my understanding correct?
Does using cross-validation with regularized cost function focus more on avoiding high variance than on avoiding high bias?
Thank you!